cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of betaselectr and tulpaRatio — release velocity, themes, recent moves, and the top alternatives to consider.
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
betaselectr computes standardised coefficients selectively, for models where blanket standardisation misleads — interaction terms, categorical predictors and moderated effects, where standardising the product term or a dummy variable produces a number that does not mean what readers assume. It has been on CRAN since November 2024 across three releases. What those releases contain cannot be determined from this feed.
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
betaselectr computes standardised coefficients selectively, for models where blanket standardisation misleads — interaction terms, categorical predictors and moderated effects, where standardising the product term or a dummy variable produces a number that does not mean what readers assume. It has been on CRAN since November 2024 across three releases. What those releases contain cannot be determined from this feed.
This changelog carries no release content. Every entry is a pointer to the CRAN page and to a changelog hosted on the package's own site, so the direction of development is not readable from what is published here. What the version numbers alone support is a package that reached CRAN in late 2024 and has issued two patch releases since, at roughly six-month intervals, without a minor version bump.
No prediction is supportable from these entries; the feed would need to carry actual release notes, or the package's own site would need to be read directly, before its direction could be called.
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
The feed reads as one architectural bet followed by the work to justify it. After the native backend landed, the releases are a steady march of gradient and adaptation work — hand-coded gradients for more model families, L-BFGS mass matrix adaptation, an O2 build — each measured as a speed multiple against Stan. Coverage is tracked openly as a fraction (48 of 60 hand-coded configs), and unresolved problems are named rather than buried, including a deferred GP spatial bug.
The hand-coded gradient coverage count is the visible backlog, so the next releases most likely close the remaining configs and resolve the GP spatial issue that the benchmark release explicitly deferred.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either betaselectr or tulpaRatio.
A choice-based IRT model published once in 2019 and kept compiling ever since
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
Rebuilding SAS's formatting layer in R, one format specification at a time
Stream-network spatial models learning to run on data that no longer fits in memory
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
See all betaselectr alternatives → · See all tulpaRatio alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. betaselectr and tulpaRatio are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. betaselectr and tulpaRatio are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top betaselectr alternatives in Analytics are ranked by recent ship velocity. Browse the "betaselectr alternatives" section above for the current picks, or visit /alternatives/betaselectr for the full list with editorial commentary on each.
Top tulpaRatio alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpaRatio alternatives" section above for the current picks, or visit /alternatives/tulparatio for the full list with editorial commentary on each.